25,136 research outputs found
Software for Wearable Devices: Challenges and Opportunities
Wearable devices are a new form of mobile computer system that provides
exclusive and user-personalized services. Wearable devices bring new issues and
challenges to computer science and technology. This paper summarizes the
development process and the categories of wearable devices. In addition, we
present new key issues arising in aspects of wearable devices, including
operating systems, database management system, network communication protocol,
application development platform, privacy and security, energy consumption,
human-computer interaction, software engineering, and big data.Comment: 6 pages, 1 figure, for Compsac 201
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Unbearable wearables
As wearable devices play an increasing role in the management of health and disease, adverse skin reactions to wearables have become more common. However, the management of allergic contact dermatitis is challenging and new treatment options more compatible with wearable devices are needed. In a 40-year-old woman with contact dermatitis to a continuous glucose monitoring device, topical clobetasol propionate 0.05% spray proved to be an effective treatment that was compatible with the application of adhesive wearables. This case demonstrates that spray formulations of topical steroids are a good option for the treatment of dermatitis under wearable devices such as continuous glucose monitors or ostomy appliance
Towards a Practical Pedestrian Distraction Detection Framework using Wearables
Pedestrian safety continues to be a significant concern in urban communities
and pedestrian distraction is emerging as one of the main causes of grave and
fatal accidents involving pedestrians. The advent of sophisticated mobile and
wearable devices, equipped with high-precision on-board sensors capable of
measuring fine-grained user movements and context, provides a tremendous
opportunity for designing effective pedestrian safety systems and applications.
Accurate and efficient recognition of pedestrian distractions in real-time
given the memory, computation and communication limitations of these devices,
however, remains the key technical challenge in the design of such systems.
Earlier research efforts in pedestrian distraction detection using data
available from mobile and wearable devices have primarily focused only on
achieving high detection accuracy, resulting in designs that are either
resource intensive and unsuitable for implementation on mainstream mobile
devices, or computationally slow and not useful for real-time pedestrian safety
applications, or require specialized hardware and less likely to be adopted by
most users. In the quest for a pedestrian safety system that achieves a
favorable balance between computational efficiency, detection accuracy, and
energy consumption, this paper makes the following main contributions: (i)
design of a novel complex activity recognition framework which employs motion
data available from users' mobile and wearable devices and a lightweight
frequency matching approach to accurately and efficiently recognize complex
distraction related activities, and (ii) a comprehensive comparative evaluation
of the proposed framework with well-known complex activity recognition
techniques in the literature with the help of data collected from human subject
pedestrians and prototype implementations on commercially-available mobile and
wearable devices
Inferring Mobile Payment Passcodes Leveraging Wearable Devices
Mobile payment has drawn considerable attention due to its convenience of paying via personal mobile devices at anytime and anywhere, and passcodes (i.e., PINs) are the first choice of most consumers to authorize the payment. This work demonstrates a serious security breach and aims to raise the awareness of the public that the passcodes for authorizing transactions in mobile payments can be leaked by exploiting the embedded sensors in wearable devices (e.g., smartwatches). We present a passcode inference system, which examines to what extent the user's PIN during mobile payment could be revealed from a single wrist-worn wearable device under different input scenarios involving either two hands or a single hand. Extensive experiments with 15 volunteers demonstrate that an adversary is able to recover a user's PIN with high success rate within 5 tries under various input scenarios
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